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A lightweight yet powerful framework for building robust data analysis pipelines. With 'pipeflow', you initialize a pipeline with your dataset and construct workflows step by step by adding R functions. You can modify, remove, or insert steps and parameters at any stage, while 'pipeflow' ensures the pipeline's integrity. Overall, this package offers a beginner-friendly framework that simplifies and streamlines the development of data analysis pipelines by making them modular, intuitive, and adaptable.
Version: | 0.2.2 |
Imports: | data.table, jsonlite, lgr, methods, R6, stats, utils |
Suggests: | ggplot2, knitr, mockery, rmarkdown, testthat, visNetwork |
Published: | 2024-12-22 |
DOI: | 10.32614/CRAN.package.pipeflow |
Author: | Roman Pahl [aut, cre] |
Maintainer: | Roman Pahl <roman.pahl at gmail.com> |
BugReports: | https://github.com/rpahl/pipeflow/issues |
License: | GPL-3 |
URL: | https://rpahl.github.io/pipeflow/, https://github.com/rpahl/pipeflow |
NeedsCompilation: | no |
Language: | en-US |
Materials: | NEWS |
In views: | ReproducibleResearch |
CRAN checks: | pipeflow results |
Package source: | pipeflow_0.2.2.tar.gz |
Windows binaries: | r-devel: pipeflow_0.2.2.zip, r-release: pipeflow_0.2.2.zip, r-oldrel: pipeflow_0.2.2.zip |
macOS binaries: | r-release (arm64): pipeflow_0.2.2.tgz, r-oldrel (arm64): pipeflow_0.2.2.tgz, r-release (x86_64): pipeflow_0.2.2.tgz, r-oldrel (x86_64): pipeflow_0.2.2.tgz |
Old sources: | pipeflow archive |
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These binaries (installable software) and packages are in development.
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